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cremp_all_flat_stats.json

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cremp_all_stats.json

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cremp_exact_stats.json

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raw/ringer/COMMIT

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raw/ringer/LICENSE

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+Copyright 2023, Genentech, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

raw/ringer/amino_acids.csv

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raw/zenodo-8010582/pickle.tar.gz

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raw/zenodo-8010582/record.json

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+{"created": "2023-06-06T20:50:55.890576+00:00", "modified": "2024-08-13T18:38:52.839540+00:00", "id": 8010582, "conceptrecid": "7931444", "doi": "10.5281/zenodo.8010582", "conceptdoi": "10.5281/zenodo.7931444", "doi_url": "https://doi.org/10.5281/zenodo.8010582", "metadata": {"title": "CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning", "doi": "10.5281/zenodo.8010582", "publication_date": "2023-05-13", "description": "<p>CREMP:&nbsp;A&nbsp;resource generated for the rapid development and evaluation of machine learning models for macrocyclic peptides. CREMP contains 36,198 unique macrocyclic peptides and their high-quality structural ensembles generated using the Conformer-Rotamer Ensemble Sampling Tool (CREST). Altogether, this dataset contains nearly 31.3 million unique macrocycle geometries, each annotated with energies derived from semi-empirical tight-binding DFT calculations. We anticipate that this dataset will enable the development of machine learning models that can improve peptide design and optimization for novel therapeutics.</p>\n<p>We provide the data in two available formats, either as Python pickle files, which provide quick read access with RDKit version 2022.09.5 or later, and as text-based SDF files with associated metadata in JSON format. Each file is named based on its amino acid sequence, with residues separated by periods, using standard one-letter codes with lowercase letters representing D-amino acids and \"Me\" prefixes representing <em>N</em>-methylated amino acids. The sequences are in no particular order, e.g., \"C.R.E.M.P\" and \"R.E.M.P.C\" correspond to the same peptide macrocycle. The filename extensions are \".pickle\", \".sdf\", and \".json\".</p>\n<p>Each file in the &ldquo;pickle&rdquo; folder contains a Python dictionary with amino acid sequence, SMILES, CREST metadata, and a single RDKit molecule object containing all conformers. All files in the folder were compressed into a single &ldquo;pickle.tar.gz&rdquo; archive. In the &ldquo;sdf_and_json&rdquo; folder, each individual SDF file contains all conformers, each associated with its own JSON file that contains CREST metadata. Similarly, all are compressed into another single archive, &ldquo;sdf_and_json.tar.bz2&rdquo;. A single summary CSV file is also provided containing &rdquo;sequence&rdquo;, &ldquo;smiles&rdquo;, &ldquo;num_monomers&rdquo;, &ldquo;num_atoms&rdquo;, &ldquo;num_heavy_atoms&rdquo;, along with the CREST metadata &ldquo;totalconfs&rdquo;, &ldquo;uniqueconfs&rdquo;, &ldquo;lowestenergy&rdquo;, &ldquo;poplowestpct&rdquo;, &ldquo;temperature&rdquo;, &ldquo;ensembleenergy&rdquo;, &ldquo;ensembleentropy&rdquo;, and &ldquo;ensemblefreeenergy&rdquo;. The number of unique conformers with different 3D structures is given by &ldquo;uniqueconfs&rdquo;, while &ldquo;totalconfs&rdquo; includes the number of rotamers in addition.</p>\n<p>The unzipped sizes of the archives are approximately 32 GB for \"pickle.tar.gz\" and 210 GB for \"sdf_and_json.tar.bz2\". If you encounter errors when trying to load the pickle files, please make sure your RDKit version is at least 2022.09.5. If that doesn't work, try other Python versions.</p>", "access_right": "open", "creators": [{"name": "Grambow, Colin A.", "affiliation": "Prescient Design, Genentech", "orcid": "0000-0002-2204-9046"}, {"name": "Weir, Hayley", "affiliation": "Prescient Design, Genentech", "orcid": "0000-0002-1039-327X"}, {"name": "Cunningham, Christian N.", "affiliation": "Department of Peptide Therapeutics, Genentech", "orcid": "0000-0003-3993-660X"}, {"name": "Biancalani, Tommaso", "affiliation": "Biology Research | AI Development, Genentech", "orcid": "0000-0001-9104-9755"}, {"name": "Chuang, Kangway V.", "affiliation": "Prescient Design, Genentech", "orcid": "0000-0002-0652-8071"}], "keywords": ["macrocycles", "conformers", "machine learning", "peptides"], "related_identifiers": [{"identifier": "10.1038/s41597-024-03698-y", "relation": "isPublishedIn", "resource_type": "publication-article", "scheme": "doi"}, {"identifier": "10.48550/arXiv.2305.19800", "relation": "isCitedBy", "resource_type": "publication-preprint", "scheme": "doi"}], "version": "1.0.1", "custom": {"code:codeRepository": "https://github.com/Genentech/cremp", "code:programmingLanguage": [{"id": "python", "title": {"en": "Python"}}]}, "resource_type": {"title": "Dataset", "type": "dataset"}, "journal": {"pages": "859", "title": "Scientific Data", "volume": "11"}, "license": {"id": "cc-by-4.0"}, "relations": {"version": [{"index": 1, "is_last": true, "parent": {"pid_type": "recid", "pid_value": "7931444"}}]}, "notes": "This version fixes the corrupted pickle.tar.gz file."}, "title": "CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning", "links": {"self": "https://zenodo.org/api/records/8010582", "self_html": "https://zenodo.org/records/8010582", "preview_html": "https://zenodo.org/records/8010582?preview=1", "doi": "https://doi.org/10.5281/zenodo.8010582", "self_doi": "https://doi.org/10.5281/zenodo.8010582", "self_doi_html": "https://zenodo.org/doi/10.5281/zenodo.8010582", "reserve_doi": "https://zenodo.org/api/records/8010582/draft/pids/doi", "parent": "https://zenodo.org/api/records/7931444", "parent_html": "https://zenodo.org/records/7931444", "parent_doi": "https://doi.org/10.5281/zenodo.7931444", "parent_doi_html": "https://zenodo.org/doi/10.5281/zenodo.7931444", "self_iiif_manifest": "https://zenodo.org/api/iiif/record:8010582/manifest", "self_iiif_sequence": "https://zenodo.org/api/iiif/record:8010582/sequence/default", "files": "https://zenodo.org/api/records/8010582/files", "media_files": "https://zenodo.org/api/records/8010582/media-files", "archive": "https://zenodo.org/api/records/8010582/files-archive", "archive_media": "https://zenodo.org/api/records/8010582/media-files-archive", "latest": "https://zenodo.org/api/records/8010582/versions/latest", "latest_html": "https://zenodo.org/records/8010582/latest", "versions": "https://zenodo.org/api/records/8010582/versions", "draft": "https://zenodo.org/api/records/8010582/draft", "access_links": "https://zenodo.org/api/records/8010582/access/links", "access_grants": "https://zenodo.org/api/records/8010582/access/grants", "access_users": "https://zenodo.org/api/records/8010582/access/users", "access_request": "https://zenodo.org/api/records/8010582/access/request", "access": "https://zenodo.org/api/records/8010582/access", "communities": "https://zenodo.org/api/records/8010582/communities", "communities-suggestions": "https://zenodo.org/api/records/8010582/communities-suggestions", "request_deletion": "https://zenodo.org/api/records/8010582/request-deletion", "file_modification": "https://zenodo.org/api/records/8010582/file-modification", "quota_increase": "https://zenodo.org/api/records/8010582/quota-increase", "requests": "https://zenodo.org/api/records/8010582/requests"}, "updated": "2024-08-13T18:38:52.839540+00:00", "recid": "8010582", "revision": 14, "files": [{"id": "1b13ac2c-a6f6-4915-94d3-5aac1fa25bb3", "key": "pickle.tar.gz", "size": 28949752920, "checksum": "md5:925d058e9d96942e5aca55b12480efc3", "links": {"self": "https://zenodo.org/api/records/8010582/files/pickle.tar.gz/content"}}, {"id": "0623e597-92df-43d3-b970-a4c23364b366", "key": "summary.csv", "size": 5961130, "checksum": "md5:6941dd885a38abefbc651bd0299c1719", "links": {"self": "https://zenodo.org/api/records/8010582/files/summary.csv/content"}}, {"id": "1cdec141-ed72-414f-9240-0e4c616d3947", "key": "sdf_and_json.tar.bz2", "size": 20531787130, "checksum": "md5:e010ecc8f5a54d886695a46b175a3a7a", "links": {"self": "https://zenodo.org/api/records/8010582/files/sdf_and_json.tar.bz2/content"}}], "swh": {}, "owners": [{"id": "546798"}], "status": "published", "stats": {"downloads": 16749, "unique_downloads": 4083, "views": 4138, "unique_views": 3795, "version_downloads": 10124, "version_unique_downloads": 2492, "version_unique_views": 2074, "version_views": 2294}, "state": "done", "submitted": true}

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